THE DASHEx LAB
동아대학교
DASHEx 연구실의 프로젝트
프로젝트 1
Customized digital CORE (COgnitive) using brain function/biodata/virtual reality for dementia prevention in the community.
치매는 고령화 사회에서 점차 더 심각한 문제가 되고 있습니다. 따라서, 다가올 초고령화 사회를 대비하자면, 이러한 노인성 질환을 예방하기 위한 방안이 시급히 필요합니다. 본 연구는 디지털 기술 및 가상현실과 같은 혁신적인 기술을 활용하여 맞춤형 치매 예방을 접근방식을 모색하고 있습니다. 이러한 방식은 뇌기능, 생체데이터 및 가상현실 기술을 활용하여 매우 첨단적이며 개인에 따라 다른 방식으로 접근할 수 있는 CORE (COgnitive Rehab Exercise) 기술을 개발하는 것입니다. 이러한 연구개발을 통해 치매 예방 및 조기 발견, 적절한 치료 및 관리를 위한 맞춤형 접근방식을 제공할 수 있을것으로 기대합니다. 더불어 이러한 연구개발은 미래의 초고령화 사회를 위해 매우 중요한 의미를 가지며, 디지털 기술과 건강과학 및 의학의 융합적인 측면에서 중요한 발전을 이루게 될 것으로 기대합니다.
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프로젝트 2
Development of virtual reality-based multisensory training solution to improve balance and cognitive function of older adults.
With the aging of society, there is an increasing need for effective health management methods to enhance the well-being and quality of life of seniors. Cognitive function, balance, posture, and sensory capabilities, such as vision and hearing, are vital factors that contribute to seniors' functional improvement and independent living. Thus, there is a growing demand for sensory training solutions that can enhance these functions. This study aims to improve the balance and cognitive function of seniors by utilizing a virtual reality-based multisensory training solution. By providing a range of sensory experiences and developing advanced technologies, this study will greatly improve balance control and cognitive abilities. The integrated sensory solution using virtual reality technology is user-friendly and can provide personalized training programs, leading to more effective results than existing traditional programs.
PROJECT 3
AI-based personalized exercise management to improve muscle function and prevent muscle loss in middle-aged people for healthy ageing.
The function of muscles is closely related to human health and independence in daily life. In particular, the decline of muscle mass and function in middle-aged and elderly individuals is associated with various health problems. Although exercise is essential as a response to this issue, it is difficult to know which exercise is appropriate for each individual. Therefore, a personalized exercise management service that can suggest exercises tailored to individual abilities is necessary. With recent advances in artificial intelligence (AI) technology, personalized exercise management services based on data collected from various sensors have become possible. In this study, we aim to develop an effective digital therapeutic technology for preventing muscle atrophy by providing optimal exercise programs based on an individual's physical characteristics, sensor-based biosignal data, and exercise capacity. Additionally, we will develop an AI-based personalized exercise management platform and service to verify their effectiveness. Through this research, we can provide the best exercise program for improving muscle function and preventing muscle atrophy in middle-aged and elderly individuals. This technological development is of great significance for improving the health and quality of life of this age group, and we expect multidisciplinary technological development in AI, exercise science, and medicine through collaborative research between medical institutions and industrial research institutions.
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PROJECT 4
Habitual Physical Activity and Musculo-skeletal Health
Physical activity is an essential component of a healthy lifestyle, and it plays a crucial role in maintaining musculoskeletal health. Skeletal muscles are important for everyday movement and are responsible for supporting the body's weight, providing mobility, and facilitating metabolic processes. However, the aging process, sedentary behavior, and certain medical conditions can lead to a loss of muscle mass and strength, and this can have a negative impact on overall health and quality of life. As a result, promoting physical activity and implementing interventions to maintain musculoskeletal health are critical for preventing age-related diseases and improving overall health outcomes. This research aims to explore the relationship between daily physical activity and musculoskeletal health, including the impact of various types of exercise on muscle strength and mass, bone density, and joint health. By examining the effects of different physical activity levels and modes on musculoskeletal health, this study aims to identify the most effective interventions for promoting and maintaining musculoskeletal health across the lifespan. Ultimately, the findings of this research have significant implications for public health initiatives and policies aimed at improving musculoskeletal health and promoting healthy aging.
PROJECT 5
Monitoring Physical Activity and Behavioral Pattern
In recent years, the importance of monitoring physical activity, sleep, behavioral patterns, and brain activity has been increasingly recognized to maintain a healthy lifestyle and improve overall well-being. Physical activity is crucial for preventing chronic diseases and maintaining physical health, while sleep quality and behavioral patterns can significantly impact one's mental health. Brain activity is also an important biomarker in understanding cognitive function and mental health. Numerous devices and technologies have been developed to monitor these factors, ranging from wearable activity trackers to EEG devices and mobile apps. This research aims to investigate the effectiveness and accuracy of various devices and technologies for monitoring physical activity, sleep, behavioral patterns, and brainwave activity. By analyzing the data collected from these devices and comparing it to self-reported measures, this study aims to identify the most reliable and effective tools for monitoring and promoting healthy lifestyles and cognitive function. The results of this research are expected to have significant implications for healthcare professionals and individuals seeking to improve their overall health and well-being through the use of these monitoring technologies.
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PROJECT 6
Prevention and Screening of Mild Cognitive Impairment
Mild cognitive impairment (MCI) is a common condition that affects many older adults and is often a precursor to more severe cognitive decline and dementia. Therefore, early detection and prevention of MCI are critical for maintaining cognitive health and preventing or delaying the onset of dementia. In recent years, there has been significant interest in developing technologies to aid in the early detection and prevention of MCI, including cognitive screening tools, brain imaging techniques, and other digital technologies. This research aims to investigate and develop new technologies for the prevention and early detection of MCI, with a particular focus on the use of digital technologies and machine learning algorithms. By combining cognitive and behavioral data with advanced machine learning algorithms, this study aims to identify new biomarkers and develop more accurate and reliable methods for detecting and preventing MCI. The results of this research are expected to have significant implications for improving cognitive health and reducing the risk of dementia, as well as for advancing the field of digital health and machine learning in the context of aging and cognitive decline.
The DASHEx Lab, S08-302, 동아대학교
37, Nakdong-daero 550beon-gil, Saha-gu, Busan, Republic of Korea (49315)